质子导电神经形态材料和设备
Yifan Yuan1, Ranjan Kumar Patel1, Suvo Banik2,3
1Department of Electrical & Computer Engineering, Rutgers, The State University of New Jersey, Piscataway, New Jersey 08854, United States.
Chemical reviews
|July 22, 2024
概括
材料中的质子兴奋剂通过模仿生物神经功能为节能神经形态计算提供了一个有前途的途径. 这篇评论探讨了用于人工智能硬件的基于质子的设备.
科学领域:
- 材料科学 材料科学 材料科学
- 神经科学是一个神经科学.
- 计算机工程 计算机工程
背景情况:
- 生物大脑使用离子电流来处理信息,激发了神经形态计算.
- 节能的人工智能硬件旨在模拟生物神经电路.
- 在电场下的质子流动性为神经形态设备提供了一个新的机制.
研究的目的:
- 审查质子在生物系统中的作用及其在神经形态计算中的潜力.
- 讨论用于神经形态结构材料中的质子兴奋剂的实验方法和机制.
- 要突出先进的表征技术和理论方法来理解这些材料中的质子行为.
主要方法:
- 对作为神经递质的质子生物类型的综述.
- 在无机和有机材料中进行质子兴奋剂的实验方法的讨论.
- 基于同步光谱学的概述,散射技术,以及用于表征的第一原则计算.
主要成果:
- 导电材料中的质子兴奋剂可以模拟生物神经功能.
- 先进的光谱和散射技术对于在固体矩阵中表征气至关重要.
- 第一原理计算提供了对质子迁移和电子结构的见解.
结论:
- 以质子为基础的神经形态电子具有节能人工智能的巨大潜力.
- 需要进一步的研究来克服先进的神经形态应用中质子兴奋剂的科学挑战.
- 了解质子迁移和电子效应是开发下一代神经形态硬件的关键.
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